Statistical Trigger Mode for Ventilator Synchrony
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Solution Overview
Problem
Conventional ventilator triggering modes struggle to accurately detect patient inspiratory efforts, particularly in chronic obstructive pulmonary disease (COPD) patients, leading to false triggers and delayed detection, which can increase the patient's work of breathing and require sedation.
Innovation Solution
The implementation of a statistical trigger mode (ST mode) that utilizes a statistical approach to improve inspiration trigger detection by monitoring parameter signals during exhalation, calculating probabilities for null and trigger hypotheses, and adjusting noise estimates to reduce false triggers and enhance detection speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional ventilator triggering modes are used, then the system is simple to operate, but false triggers and delayed detection occur leading to increased patient work of breathing
Solution Approach 1:
The patent replaces conventional mechanical/threshold-based triggering systems with a statistical computing system. The trigger module uses statistical algorithms to analyze patient effort signals, calculate probabilities for null and trigger hypotheses, and determine breath triggers based on statistical significance rather than fixed thresholds. This substitution improves reliability by reducing false triggers and delayed detection while managing complexity through software-based statistical processing.
2Speed
If conventional triggering modes are used, then the device complexity is low, but the trigger detection time is delayed (300 ms)
Solution Approach 1:
The statistical trigger module performs preliminary computational actions by continuously monitoring patient effort signals and pre-calculating statistical parameters during the exhalation phase. The system prepares probability distributions and hypothesis frameworks in advance, allowing rapid trigger detection when patient effort occurs. This preliminary statistical processing reduces the 300 ms delay by having computational structures ready before triggering is needed.
3Object-affected harmful factors
If conventional triggering modes are used, then the system is easy to operate, but false triggers occur increasing patient work of breathing
Solution Approach 1:
The statistical trigger module implements feedback mechanisms by continuously analyzing the effectiveness of trigger detection and adjusting statistical parameters accordingly. The system monitors patient responses to triggered breaths and refines its probability calculations to reduce false triggers. This feedback loop eliminates harmful false triggers that increase patient work of breathing while maintaining ease of operation through automated statistical optimization.
4Reliability
If statistical trigger mode is implemented, then false triggers are reduced and detection speed is improved, but the computational complexity increases
Solution Approach 1:
The statistical trigger module performs self-service by autonomously calculating statistical parameters, updating probability distributions, and determining trigger thresholds without requiring manual intervention. The system automatically monitors patient effort signals, computes null and trigger hypothesis probabilities, and adjusts its statistical models based on observed data. This self-service capability manages computational complexity through automated processes while maintaining high trigger detection reliability.
Data Source
AI summary
The systems and methods provide for novel a triggering mode that allows the patient to trigger or initiate the delivery of a breath during ventilation on a ventilator. Further, the systems and methods provide for triggering ventilation utilizing a statistical trigger mode. Additionally, the systems and methods provide for analyzing and/or displaying information related to a potential change in a triggering threshold for a currently utilized breath type.